Google published a research paper about helping recommender systems understand what users mean when they interact with them. Their goal with this new approach is to overcome the limitations inherent ...

Abstract: As the Netflix Prize competition has demonstrated, matrix factorization models are superior to classic nearest neighbor techniques for producing product recommendations, allowing the ...

【2020.12.20】在Top-K模型中，评估方式为正负样本1:100的模型（MF-BPR、SASRec等），之前评估代码效率太低，因此进行了调整 ...

Laurence Fishburne has addressed whether he might step back into the role of Morpheus for The Matrix 5. Appearing at New York Comic Con 2025 for The Matrix reunion panel, the actor said that he is ...

There once was a time where going viral on the internet actually meant something. Long ago, in the early 2010s, 500,000 views could actually land you on daytime TV, where you could experience the ...

ABSTRACT: The offline course “Home Plant Health Care,” which is available to the senior population, serves as the study object for this paper. Learn how to use artificial intelligence technologies to ...

Liam Gaughan is a film and TV writer at Collider. He has been writing film reviews and news coverage for ten years. Between relentlessly adding new titles to his watchlist and attending as many ...

Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix ...

Yandex has recently made a significant contribution to the recommender systems community by releasing Yambda, the world’s largest publicly available dataset for recommender system research and ...

Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, ...